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Attackers target serverless functions in the hope of exploiting vulnerabilities that arise as a result of application developers deploying insecure code and misconfiguring cloud functions. Successful exploits of these weaknesses enable attackers to obtain credentials that can then be abused. Serverless computing functions are often associated with cloud identities that use authentication tokens to gain temporary, scoped access to cloud services and resources. Exfiltrating these tokens can expose cloud environments to security risks. [Amazon Web Services (AWS) Lambda](https://aws.amazon.com/lambda/), [Azure Functions](https://learn.microsoft.com/en-us/azure/azure-functions/functions-overview?pivots=programming-language-csharp) and [Google Cloud Run Functions](https://cloud.google.com/functions?hl=en) are all examples of serverless platforms and functions that make use of credentials. These credentials include [identity and access management (IAM)](https://docs.aws.amazon.com/whitepapers/latest/introduction-aws-security/identity-and-access-control.html) roles in AWS, [managed identities](https://learn.microsoft.com/en-us/entra/identity/managed-identities-azure-resources/overview) in Azure and [service account tokens](https://cloud.google.com/iam/docs/service-account-creds) in the Google Cloud Platform (GCP). Understanding how these services operate enables us to implement effective strategies to avoid exposing tokens and to detect the abuse of exposed tokens that can lead to the compromise of cloud environments. Such compromises involve privilege escalation, malicious persistence within the environment and the exfiltration of sensitive information that only legitimate identities should be able to access. Palo Alto Networks customers are better protected through our [Cortex](https://www.paloaltonetworks.com/cortex) line of products from threats discussed in this article. Cortex Cloud provides contextual detection of the malicious operations detailed within this article using [attack path](https://docs-cortex.paloaltonetworks.com/r/Cortex-CLOUD/Cortex-Cloud-Posture-Management-Documentation/Key-features?tocId=HQSmhglbgBmaf~dPOXaTDw), or attack flow, scenario detections. This provides flexibility in defining and enforcing security policies or exceptions when faced with evolving or complex attack techniques. | **Related Unit 42 Topics** | [**Amazon Web Services**](https://unit42.paloaltonetworks.com/tag/aws/), **[Microsoft Azure](https://unit42.paloaltonetworks.com/tag/microsoft-azure/)** , **[Google Cloud](https://unit42.paloaltonetworks.com/tag/google-cloud/)** | |----------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| ## Introduction Serverless computing is a cloud model where providers like AWS (Lambda), Azure (Functions) and Google Cloud (Functions) manage infrastructure, scaling and maintenance. This model enables organizations and their developers to focus solely on code, while the cloud provider handles backend tasks. Operating on an event-driven basis, serverless functions execute in response to triggers like HTTP requests, database changes or scheduled events. The function service's automated scaling adjusts resources to match demand, ensuring cost efficiency by the cloud provider only charging for execution time and resources used. While serverless computing simplifies development and deployment, it is important to understand the potential risks associated with these services. Some of those risks arise from the fact that developers can assign identities to serverless functions, and those identities are manifested as credential sets that are accessible to the code executing within the function. These credentials are used for authentication and authorization to perform cloud operations. These credentials are applied with a set of permissions that dictate their use. Depending on the permissions associated with the identity attached to the function, those credentials can enable access to cloud resources and sensitive data. Attackers target serverless functions for these reasons: * Serverless functions can often be vulnerable to remote code execution (RCE) or server-side request forgery (SSRF) attacks due to insecure development practices * Serverless functions are often publicly exposed (either by design or due to misconfiguration) or process inputs from external sources * Attackers can exploit serverless tokens to obtain unauthorized read/write access that could potentially jeopardize critical infrastructure and data When using serverless functions, it is important to consider the risks involved when application developers deploy insecure code to cloud functions, and to understand the threats that target these functions. ## How Serverless Authentication Works in Major Cloud Platforms Using the serverless approach, applications are deployed by executing functions on demand. The primary advantage of this approach is that applications or specific components can be run on an as-needed basis, eliminating the need for a continuously running execution environment. Each of the major cloud providers shares similar concepts for serverless functions, such as: * Support for multiple code languages * The absence of SSH access due to their fully managed architecture * Using roles, service accounts or managed identities to securely manage resource access ### AWS Lambda The IAM service in AWS enables the creation and management of users, permissions, groups and roles. The service is responsible for managing identities and their level of access to AWS accounts and services, and control of various features within an AWS account. Serverless functions use Lambda roles, which do not have default permissions; IAM policies must be used to manage permissions and secure access to other AWS services. To make permission management simpler, AWS provides managed policies (like AWSLambdaBasicExecutionRole) that developers often attach to these roles to quickly enable basic functionality. When an IAM role is associated with a Lambda function, the AWS [Security Token Service (STS)](https://docs.aws.amazon.com/STS/latest/APIReference/welcome.html) automatically generates [temporary security credentials](https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp.html) for that role. This is a secure way to get access to credentials at runtime without the risks associated with long-term, hard-coded credentials. These credentials are scoped to the permissions defined in the role's associated access policy. They include an access key ID, secret access key and session token. At runtime, the Lambda runtime service loads the role credentials into the function's execution environment and stores them as environment variables, such as AWS\_ACCESS\_KEY\_ID, AWS\_SECRET\_ACCESS\_KEY and AWS\_SESSION\_TOKEN. These variables are accessible to the code of the function during runtime, allowing the function to interact securely with other AWS services. ### Google Cloud Functions Google Cloud Functions use service account tokens to authenticate and authorize access to other Google Cloud services. A service account is a specialized Google account that is tied to a [project](https://cloud.google.com/storage/docs/projects) and represents a non-human identity, rather than to an individual user. When deploying a Cloud Function, developers can attach the function to a custom service account or the [default service account](https://cloud.google.com/iam/docs/service-account-types#default). When using a custom service account, developers can assign specific IAM roles to define the exact permissions the function requires to perform its tasks. Default service accounts are [user-managed accounts](https://cloud.google.com/compute/docs/access/service-accounts#user-managed) that Google Cloud automatically creates when users enable specific services. By default, Google Cloud Functions use different service accounts [depending on the generation](https://cloud.google.com/run/docs/functions/comparison): * First-generation Cloud Run functions use the App Engine default service account (\@appspot.gserviceaccount.com) * Second-generation Cloud Run functions use the Default Compute service account (\-compute@developer.gserviceaccount.com) These default service accounts are granted editor permissions when developers are onboarding to GCP without an organization, allowing them to create, modify and delete resources within the project. However, in projects under a GCP organization, default service accounts are created without any permissions. In such cases, they can only perform actions that are explicitly allowed by the roles assigned to them. Although a GCP Function operates in a serverless environment, when it comes to accessing the credentials associated with the function, it behaves similarly to a traditional server, such as a virtual machine (VM) instance, by retrieving its service account tokens from the [Instance Metadata Server (IMDS)](https://cloud.google.com/run/docs/container-contract#metadata-server) at runtime. The IMDS at hxxp://metadata.google\[.\]internal/ provides short-lived access tokens for the function's associated service account. These tokens enable the function to authenticate to GCP services. ### Azure Functions Azure managed identities provide a secure and seamless way for Azure resources to authenticate to and interact with other Azure services without the need for hard-coded credentials. In the same way as AWS and GCP's function services, these identities eliminate the risks associated with managing credentials in code. System-assigned managed identities are tied to a single resource and automatically deleted when the resource is removed. On the other hand, user-assigned managed identities are independent resources that can be assigned to multiple services, offering more flexibility for shared authentication scenarios. An Azure Function with a managed identity attached to it should use its managed identity token to authenticate to an Azure resource. The step-by-step authentication process is as follows: * The function queries its environment variables to retrieve the values of IDENTITY\_ENDPOINT and IDENTITY\_HEADER. * IDENTITY\_ENDPOINT: An [environment variable](https://learn.microsoft.com/en-us/azure/app-service/reference-app-settings?tabs=kudu%2Cdotnet#identity) that contains the address of the local managed identity endpoint provided by Azure. This is a local URL from which an app can request tokens. * IDENTITY\_HEADER: A required parameter when querying the local managed identity endpoint. This header is used to help mitigate SSRF attacks. * The function sends an HTTP GET request to the local managed identity endpoint with the IDENTITY\_HEADER included as an HTTP header. (For details on the request structure, refer to [Azure's documentation on acquiring tokens for App Services](https://learn.microsoft.com/en-us/azure/app-service/overview-managed-identity?tabs=portal%2Cdotnet#using-the-rest-protocol)) * [Microsoft Entra ID](https://learn.microsoft.com/en-us/entra/fundamentals/whatis) (formerly Azure Active Directory) verifies the function's identity and issues a temporary OAuth 2.0 token that is scoped specifically for the target resource. * The function includes the issued token in its request to the Azure resource (e.g., [Azure Key Vault](https://learn.microsoft.com/en-us/azure/key-vault/general/overview), [Storage Account](https://learn.microsoft.com/en-us/azure/storage/common/storage-account-overview)). * The Azure resource validates the token and checks the function's permissions using [role-based access control](https://learn.microsoft.com/en-us/azure/role-based-access-control/overview), or [resource-specific access policies](https://learn.microsoft.com/en-us/azure/key-vault/general/secure-your-key-vault#access-policies-vs-azure-rbac). If authorized, the resource grants access to perform the requested operation. This ensures secure and seamless authentication without the need to use hard-coded secrets in the code. ## Token Exfiltration Attack Vectors This section discusses the risks and threats involved in the use of serverless functions. When developing and configuring functions, application developers should be sure to secure those functions against attacks like SSRF and RCE. In the absence of such security, attackers could manipulate serverless functions that are vulnerable to SSRF, causing the functions to send unauthorized requests to internal services. This can lead to unintended access or exposure of sensitive information within the system, such as access tokens, internal database content or service configurations. It is important to emphasise that these risks primarily arise when functions are public, or process inputs from external users and other sources. In SSRF attacks, an attacker tricks a server (like a serverless function) into making HTTP requests to internal or external resources that the attacker shouldn't have access to. Since the server itself makes the request, it can access internal services that are not exposed to the internet. A vulnerable serverless function takes a URL as input and fetches data from it. In GCP, SSRF can be used to access the IMDS at hxxp://metadata.google\[.\]internal/, extracting short-lived service account tokens. An attacker can then leverage these tokens to impersonate the function and perform unauthorized actions within its IAM role's permissions. Remote code execution vulnerabilities allow attackers to execute arbitrary code within a function's environment. For AWS Lambda, RCE attacks could expose temporary credentials stored in environment variables, such as AWS\_ACCESS\_KEY\_ID and AWS\_SESSION\_TOKEN. It is essential to note that these attack vectors are not inherent flaws in the cloud platforms themselves, but rather arise from insecure code written by application developers that could introduce vulnerabilities, such as SSRF or RCE. Application developers can mitigate these risks by implementing secure coding practices such as input validation. ### Attack Vector Simulations The following simulations demonstrate possible ways attackers could extract serverless tokens and use them for malicious activities in different cloud service providers (CSPs). These attacks could leverage unsecure function code that was deployed by application developers. #### Simulation 1: Gaining Direct Access to IMDS from GCP Function To conduct this simulation, we deployed two Google Cloud Run functions that access the function metadata service and extract the tokens of the two different attached service accounts from the following path: * hxxp\[://\]metadata.google\[.\]internal/computeMetadata/v1/instance/service-accounts/default/token The first example demonstrates the extraction of a default service account. The second example demonstrates the extraction of a custom service account. These examples show how code can directly access the metadata service, just as a vulnerable SSRF code application could access it as well. ##### **Example 1: Extracting a GCP Default Service Account** As shown in Figure 1, the service account attached to the function was the default serverless service account. Figure 2 demonstrates that the returned access token belongs to the same service account. ![Screen capture of a General Information section displaying deployment specifications including deployment date, region as US-central1, memory allocated at 256 MiB, CPU usage, timeout period, minimum and maximum instances, concurrency, and a service account email address with some information redacted.](https://unit42.paloaltonetworks.com/wp-content/uploads/2025/06/word-image-881527-143156-1.png) Figure 1. General information about the function, including an attached service account name (the default service account). ![Screenshot of a command line interface executing a cURL command to a Google Cloud function, including partial visibility of an access token and a service account email address. Many lines are redacted.](https://unit42.paloaltonetworks.com/wp-content/uploads/2025/06/word-image-885015-143156-2.png) Figure 2. Code snippet of a command used to extract the service account access token, including the output. ##### **Example 2: Extracting a GCP Custom Service Account** Figure 3 shows the custom service account that we attached to the function. Figure 4 shows the returned access token belonging to the custom service account. We then used the returned token to perform operations in the environment. ![Screenshot showing general information of a deployment in Google Cloud Platform, including last deployment date, region, memory, CPU allocation, and other service details. Some of the email address is redacted.](https://unit42.paloaltonetworks.com/wp-content/uploads/2025/06/word-image-888996-143156-3.png) Figure 3. General information about the function, including the attached service account name (a custom service account). ![Screenshot of a command line interface using cURL to make an API request to IBM's cloud functions, including partial visibility of an authorization token and a service account email. Many lines are redacted.](https://unit42.paloaltonetworks.com/wp-content/uploads/2025/06/word-image-891665-143156-4.png) Figure 4. Code snippet of a command used to extract the service account access token, including the output. Figure 5 below shows an example of a command to list buckets. ![Screenshot of code input for accessing a Google Cloud Storage API using a curl command with authorization token.](https://unit42.paloaltonetworks.com/wp-content/uploads/2025/06/word-image-894838-143156-5.png) Figure 5. Using the returned token to list buckets in a service account. If attackers can list and read bucket contents in GCP, they can access sensitive files like credentials, backups or internal configurations. This allows them to steal data, compromise the system or move laterally within the environment. Once attackers obtain an access token for a service account with Editor permissions in GCP (such as the default Compute Engine service account), they can modify, delete or create resources across most services. This includes accessing sensitive data, deploying malicious workloads, escalating privileges or disrupting services. Editor access effectively grants near-full control over the project. #### Simulation 2: Using RCE to Retrieve Tokens Stored in AWS Lambda Function Environment Variables In this simulation, we accessed the environment variables of the Lambda function and extracted from it the AWS\_ACCESS\_KEY\_ID, AWS\_SECRET\_ACCESS\_KEY and AWS\_SESSION\_TOKEN. Figure 6 shows the output of the Lambda function code. ![Screenshot displaying a code snippet with environment variables, with their values partially redacted.](https://unit42.paloaltonetworks.com/wp-content/uploads/2025/06/word-image-897519-143156-6.png) Figure 6. The values of the returned environment variables. Figure 7 shows the setup of temporary AWS credentials obtained from the previous step (the Lambda environment variables). ![Screen showing a list of timestamps and command lines with partial redactions for security. The background is dark with white text.](https://unit42.paloaltonetworks.com/wp-content/uploads/2025/06/word-image-900167-143156-7.png) Figure 7. Code snippet of commands used to list S3 buckets. Then we used the following command to list all S3 buckets the authenticated session could access. aws s3 ls |---|-----------| | 1 | aws s3 ls | #### Simulation 3: Using RCE to Retrieve Tokens From Local Identity Endpoint of an Azure Function In this simulation, we accessed the environment variables of the Azure function and extracted the IDENTITY\_ENDPOINT and the IDENTITY\_HEADER by executing remote commands. Then we extracted the managed identity token from the local identity endpoint, providing these parameters shown below in Figure 8: * Resource * api-version * X-IDENTITY-HEADER ![Screenshot of code on a black background. Some of the lines are redacted for security concerns. The visible information includes timestamps and more.](https://unit42.paloaltonetworks.com/wp-content/uploads/2025/06/word-image-903560-143156-8.png) Figure 8. The script output, including the access token. ## Detecting and Preventing Token Exfiltration ### Detecting Token Exfiltration in Serverless Environments Effective detection mechanisms are critical for identifying token exfiltration in serverless environments. These mechanisms focus on behavior anomalies to flag unauthorized activities. The following are some of the key detection strategies implemented across major cloud platforms. Detection consists of two stages: * Validating that the identity is attached to a serverless function * Identifying anomalous behavior of the serverless identities. Such behavior could include: * Source IP addresses that do not suit the context in which the function is executing, such as addresses from Autonomous System Numbers (ASNs) that are not associated with a cloud provider * Serverless identities making requests with suspicious user agents #### Step 1: Identifying Serverless Identities To identify service accounts attached to serverless functions in GCP, we analyze the serviceAccountDelegationInfo section in the logs. This information provides crucial insights into the delegation chain of service accounts. Specifically, when a service account is attached to a function, it delegates its authority to a default serverless service account: * Google Cloud Run Service Agent (service-\@serverless-robot-prod.iam.gserviceaccount\[.\]com) * gcf-admin-robot.iam.gserviceaccount\[.\]com (service-PROJECT\_NUMBER@gcf-admin-robo.iam.gserviceaccount\[.\]com) These service accounts execute tasks on behalf of the function. For example, in the log entry in Figure 9, we see the custom service account that was attached to a function (sa-test@\.iam.gserviceaccount\[.\]com) delegating its authority to the Cloud Run Service Agent. ![A screenshot of a code snippet displaying various details, including email addresses and service names for Google APIs.](https://unit42.paloaltonetworks.com/wp-content/uploads/2025/06/word-image-906421-143156-9.png) Figure 9. Log entry showing custom service account. In Figure 9 above, the principalEmail field under authenticationInfo specifies the service account being used (sa-test\[@\]xdr-analytics.iam.gserviceaccount\[.\]com). The serviceAccountDelegationInfo shows the first-party principal (in this case: service-\@serverless-robot-prod.iam.gserviceaccount\[.\]com), indicating that the service account is operating within a serverless environment like Cloud Functions or Cloud Run. An effective approach to discover serverless identities is to profile service accounts that have previously delegated their authority to default serverless service accounts. This ensures that even if non-default service accounts are attached to functions, they are identified. In AWS, Lambda functions rely on IAM roles for secure access to AWS services. These roles generate temporary credentials. We can identify the Lambda identity by its role name. In Azure, managed identities attached to Azure Function Apps are used for authentication. #### Step 2: Identifying Unusual Behavior for Serverless Identities In a secure cloud environment, serverless functions are typically intended to perform automated, scoped tasks such as responding to API requests or processing events. These functions are not to be used interactively. However, if attackers gain access to a serverless function's environment or its identity, they might misuse it to run command-line interface (CLI) commands (e.g., gcloud CLI or curl) to interact with cloud resources directly. One form of detection is to analyze the user agent of API calls. If the user agent matches known CLI tools (e.g., gcloud CLI) or penetration testing frameworks, it is flagged as suspicious, as CLI should not usually be used by serverless identities. This indicates potential exploitation of the environment or service account tokens. Of note, this method of identifying remote use of serverless tokens according to the user agent cannot be performed in Azure, because user agent information does not appear in Azure logs. Another approach for detecting remote use of a serverless identity token is to correlate the location of a token's use with ASN ranges of known cloud provider IP addresses. If a request originates from an external IP address not associated with the CSP, it triggers an alert, highlighting potential unauthorized token usage outside the cloud environment. ### Prevention Strategies Securing serverless tokens requires a combination of proactive measures, posture management and runtime monitoring security practices to minimize the risk of exploitation. First, implement the principle of least privilege by assigning roles with the minimum required permissions for serverless functions. This reduces the potential impact of token misuse. Additionally, to protect serverless runtime environments in GCP and Azure, restrict access to IMDS by configuring network-level controls and applying request validation mechanisms. Ensure robust input validation and sanitization to prevent attackers from using exploitation techniques like SSRF to access sensitive metadata, tokens and other cloud resources like APIs and databases. ## Conclusion Serverless computing is the preferred choice for modern application development because it offers significant advantages in scalability, cost-efficiency and simplified infrastructure management. The credentials that enable these functions to interact with cloud services are a critical security element and a prime target for attackers. Compromising these credentials can lead to severe consequences, including unauthorized access to cloud resources and data exfiltration. Implementing proactive posture management and runtime monitoring protections is a crucial strategy in protecting cloud environments. Organizations can better protect their serverless environments by: * Understanding the mechanics of serverless credentials and best practices to provision and manage them in AWS, Azure and [GCP](https://cloud.google.com/iam/docs/best-practices-service-accounts#limit-service-account-privileges) * Recognizing common attack vectors like token exfiltration via IMDS exploitation or environment variable access ## Palo Alto Networks Protection and Mitigation Palo Alto Networks customers are better protected from the threats discussed above through the following product: Cortex Cloud provides contextual detection of the malicious operations detailed within this article using [attack path](https://docs-cortex.paloaltonetworks.com/r/Cortex-CLOUD/Cortex-Cloud-Posture-Management-Documentation/Key-features?tocId=HQSmhglbgBmaf~dPOXaTDw), or attack flow, scenario detections. This provides flexibility in defining and enforcing security policies or exceptions when faced with evolving or complex attack techniques. If you think you may have been compromised or have an urgent matter, get in touch with the[Unit 42 Incident Response team](https://start.paloaltonetworks.com/contact-unit42.html) or call: * North America Toll-Free: 866.486.4842 (866.4.UNIT42) * EMEA: +31.20.299.3130 * APAC: +65.6983.8730 * Japan: +81.50.1790.0200 Palo Alto Networks has shared these findings with our fellow Cyber Threat Alliance (CTA) members. CTA members use this intelligence to rapidly deploy protections to their customers and to systematically disrupt malicious cyber actors. Learn more about the [Cyber Threat Alliance](https://www.cyberthreatalliance.org). ## Additional Resources * [Working with Lambda environment variables](https://docs.aws.amazon.com/lambda/latest/dg/configuration-envvars.html) -- AWS Lambda Development Guide * [Securing Lambda environment variables](https://docs.aws.amazon.com/lambda/latest/dg/configuration-envvars-encryption.html) -- AWS Lambda Development Guide * [Managing permissions in AWS Lambda](https://docs.aws.amazon.com/lambda/latest/dg/lambda-permissions.html) -- AWS Lambda Development Guide * [Function Identity](https://cloud.google.com/functions/docs/securing/function-identity) -- Google Cloud * [What are managed identities for Azure resources?](https://learn.microsoft.com/en-us/azure/active-directory/managed-identities-azure-resources/overview) -- Microsoft Learn * [Securing Azure Functions](https://learn.microsoft.com/en-us/azure/azure-functions/security-concepts) -- Microsoft Learn * [What is AWS Secrets Manager?](https://docs.aws.amazon.com/secretsmanager/latest/userguide/intro.html) -- AWS Secret Manager User Guide * [Azure Key Vault basic concepts](https://learn.microsoft.com/en-us/azure/key-vault/general/basic-concepts) -- Microsoft Learn * [Secret Manager overview](https://cloud.google.com/secret-manager/docs/overview) -- Google Cloud Secret Manager Documentation * [What is identity and access management (IAM)?](https://www.microsoft.com/en-us/security/business/security-101/what-is-identity-access-management-iam) -- Microsoft Security * [What are managed identities for Azure resources?](https://learn.microsoft.com/en-us/entra/identity/managed-identities-azure-resources/overview) -- Microsoft Learn * [Identity and Access Control](https://docs.aws.amazon.com/whitepapers/latest/introduction-aws-security/identity-and-access-control.html) -- Introduction to AWS Security AWS Whitepaper * [Service account credentials](https://cloud.google.com/iam/docs/service-account-creds) -- Google Cloud IAM Documentation * [Temporary security credentials in IAM](https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp.html) -- AWS Identity and Access Management User Guide * [AWS Security Token Service API Reference](https://docs.aws.amazon.com/STS/latest/APIReference/welcome.html) -- AWS Security Token Service Documentation * [Compute Engine instances](https://cloud.google.com/compute/docs/instances) -- Google Cloud Documentation * [Google Cloud Projects](https://cloud.google.com/storage/docs/projects) -- Google Cloud Documentation * [User-managed service accounts](https://cloud.google.com/compute/docs/access/service-accounts#user-managed) -- Google Cloud Documentation * [Compare Cloud Run functions](https://cloud.google.com/run/docs/functions/comparison) -- Google Cloud Run Documentation * [Default service accounts](https://cloud.google.com/iam/docs/service-account-types#default) -- Google Cloud Documentation * [REST endpoint reference](https://learn.microsoft.com/en-us/azure/app-service/overview-managed-identity?tabs=portal%2Chttp#rest-endpoint-reference) -- Managed Identities for App Service and Azure Functions * [Environment variables and app settings in Azure App Service](https://learn.microsoft.com/en-us/azure/app-service/reference-app-settings?tabs=kudu%2Cdotnet#identity) -- Microsoft Learn * [How to use managed identities for Azure resources on an Azure VM to acquire an access token](https://learn.microsoft.com/en-us/entra/identity/managed-identities-azure-resources/how-to-use-vm-token#app-service-and-azure-functions) -- Microsoft Learn * [What is Microsoft Entra ID?](https://learn.microsoft.com/en-us/entra/fundamentals/whatis) -- Microsoft Learn * [About Azure Key Vault](https://learn.microsoft.com/en-us/azure/key-vault/general/overview) -- Microsoft Learn * [Authorize access to blobs using Microsoft Entra ID](https://learn.microsoft.com/en-us/azure/storage/blobs/authorize-access-azure-active-directory) -- Microsoft Learn * [Storage account overview](https://learn.microsoft.com/en-us/azure/storage/common/storage-account-overview) -- Microsoft Learn * [What is Azure role-based access control (Azure RBAC)?](https://learn.microsoft.com/en-us/azure/role-based-access-control/overview) -- Microsoft Learn * [Resource-specific access policies](https://learn.microsoft.com/en-us/azure/key-vault/general/secure-your-key-vault#access-policies-vs-azure-rbac) -- Microsoft Learn Back to top ### Tags * [AWS](https://unit42.paloaltonetworks.com/tag/aws/ "AWS") * [Google Cloud](https://unit42.paloaltonetworks.com/tag/google-cloud/ "Google Cloud") * [Microsoft Azure](https://unit42.paloaltonetworks.com/tag/microsoft-azure/ "Microsoft Azure") * [Serverless](https://unit42.paloaltonetworks.com/tag/serverless/ "serverless") [Threat Research Center](https://unit42.paloaltonetworks.com "Threat Research") [Next: JSFireTruck: Exploring Malicious JavaScript Using JSF\*ck as an Obfuscation Technique](https://unit42.paloaltonetworks.com/malicious-javascript-using-jsfiretruck-as-obfuscation/ "JSFireTruck: Exploring Malicious JavaScript Using JSF*ck as an Obfuscation Technique") ### Table of Contents * ### Related Articles * [Pass the Passkey: A Novel Attack Surface in Passwordless Authentication](https://unit42.paloaltonetworks.com/passwordless-authentication-security-risks/ "article - table of contents") * [The Global Namespace Risk: Universal Bucket Hijacking Technique for Cloud Data Exfiltration](https://unit42.paloaltonetworks.com/cloud-bucket-hijacking-risks/ "article - table of contents") * [Pickle in the Middle -- Hijacking Vertex AI Model Uploads for Cross-Tenant RCE](https://unit42.paloaltonetworks.com/hijacking-vertex-ai-model/ "article - table of contents") ## Related Cloud Cybersecurity Research Resources ![Pictorial representation of bucket hijacking technique for cloud data exfiltration. Digital illustration of Europe map highlighting network connections and nodes, depicted as glowing points and lines on a dark blue background, emphasizing major cities and connectivity across the continent.](https://unit42.paloaltonetworks.com/wp-content/uploads/2026/06/09_Cloud_cybersecurity_research_Overview_1920x900-786x368.jpg) [![category icon](https://unit42.paloaltonetworks.com/wp-content/uploads/2024/06/icon-threat-research.svg)Threat Research](https://unit42.paloaltonetworks.com/category/threat-research/) June 22, 2026 [#### The Global Namespace Risk: Universal Bucket Hijacking Technique for Cloud Data Exfiltration](https://unit42.paloaltonetworks.com/cloud-bucket-hijacking-risks/) * [AWS](https://unit42.paloaltonetworks.com/tag/aws/ "AWS") * [Bucket hijacking](https://unit42.paloaltonetworks.com/tag/bucket-hijacking/ "bucket hijacking") * [Cloud data exfiltration](https://unit42.paloaltonetworks.com/tag/cloud-data-exfiltration/ "cloud data exfiltration") [Read now ![Right arrow](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-right-arrow-withtail.svg)](https://unit42.paloaltonetworks.com/cloud-bucket-hijacking-risks/ "The Global Namespace Risk: Universal Bucket Hijacking Technique for Cloud Data Exfiltration") ![Pictorial representation of Vertex AI model uploads. Close-up view of a digital wall displaying various glowing icons, representing a high-tech network interface.](https://unit42.paloaltonetworks.com/wp-content/uploads/2026/06/AdobeStock_1270203474-1-786x354.png) [![category icon](https://unit42.paloaltonetworks.com/wp-content/uploads/2024/06/icon-threat-research.svg)Threat Research](https://unit42.paloaltonetworks.com/category/threat-research/) June 16, 2026 [#### Pickle in the Middle -- Hijacking Vertex AI Model Uploads for Cross-Tenant RCE](https://unit42.paloaltonetworks.com/hijacking-vertex-ai-model/) * [Bucket squatting](https://unit42.paloaltonetworks.com/tag/bucket-squatting/ "bucket squatting") * [Google Cloud](https://unit42.paloaltonetworks.com/tag/google-cloud/ "Google Cloud") * [Joblib](https://unit42.paloaltonetworks.com/tag/joblib/ "joblib") [Read now ![Right arrow](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-right-arrow-withtail.svg)](https://unit42.paloaltonetworks.com/hijacking-vertex-ai-model/ "Pickle in the Middle – Hijacking Vertex AI Model Uploads for Cross-Tenant RCE") ![Pictorial representation of Cloud Logging services for defense evasion. A vibrant digital illustration depicting a glowing, neon blue cloud symbol positioned over a circuit board landscape. The cloud symbolizes cloud computing technology, and the landscape features intricate electronic circuits with glowing lines and nodes, suggesting high-tech data transfer and connectivity.](https://unit42.paloaltonetworks.com/wp-content/uploads/2026/06/11_Cloud_cybersecurity_research_Overview_1920x900-786x368.jpg) [![category icon](https://unit42.paloaltonetworks.com/wp-content/uploads/2024/06/icon-threat-research.svg)Threat Research](https://unit42.paloaltonetworks.com/category/threat-research/) June 9, 2026 [#### Blinding the Watchmen: Abusing Cloud Logging Services for Defense Evasion and Visibility](https://unit42.paloaltonetworks.com/cloud-logging-defense-evasion/) * [AWS CloudTrail](https://unit42.paloaltonetworks.com/tag/aws-cloudtrail/ "AWS CloudTrail") * [Cloud logging](https://unit42.paloaltonetworks.com/tag/cloud-logging/ "cloud logging") * [Defense evasion](https://unit42.paloaltonetworks.com/tag/defense-evasion/ "defense evasion") [Read now ![Right arrow](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-right-arrow-withtail.svg)](https://unit42.paloaltonetworks.com/cloud-logging-defense-evasion/ "Blinding the Watchmen: Abusing Cloud Logging Services for Defense Evasion and Visibility") ![Pictorial representation of ROADtools framework in the cloud. An Asian man wearing glasses sits in front of a computer screen. Reflecting in the glasses are lines indicating analysis. Bright blue city lights illuminate the rest of the image.](https://unit42.paloaltonetworks.com/wp-content/uploads/2026/05/10_Cloud_cybersecurity_research_Overview_1920x900-1-786x368.jpg) [![category icon](https://unit42.paloaltonetworks.com/wp-content/uploads/2024/06/icon-threat-research.svg)Threat Research](https://unit42.paloaltonetworks.com/category/threat-research/) May 22, 2026 [#### Paved With Intent: ROADtools and Nation-State Tactics in the Cloud](https://unit42.paloaltonetworks.com/roadtools-cloud-attacks/) * [Curious Serpens](https://unit42.paloaltonetworks.com/tag/curious-serpens/ "Curious Serpens") * [Entra ID](https://unit42.paloaltonetworks.com/tag/entra-id/ "Entra ID") * [Microsoft Azure](https://unit42.paloaltonetworks.com/tag/microsoft-azure/ "Microsoft Azure") [Read now ![Right arrow](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-right-arrow-withtail.svg)](https://unit42.paloaltonetworks.com/roadtools-cloud-attacks/ "Paved With Intent: ROADtools and Nation-State Tactics in the Cloud") ![Pictorial representation of autonomous AI attack in cloud environments. Digital illustration of a glowing blue brain connected to a network of lines and lights.](https://unit42.paloaltonetworks.com/wp-content/uploads/2026/04/12_Cloud_cybersecurity_research_Overview_1920x900-786x368.jpg) [![category icon](https://unit42.paloaltonetworks.com/wp-content/uploads/2024/06/icon-threat-research.svg)Threat Research](https://unit42.paloaltonetworks.com/category/threat-research/) April 23, 2026 [#### Can AI Attack the Cloud? Lessons From Building an Autonomous Cloud Offensive Multi-Agent System](https://unit42.paloaltonetworks.com/autonomous-ai-cloud-attacks/) * [AI](https://unit42.paloaltonetworks.com/tag/ai/ "AI") * [Cloud](https://unit42.paloaltonetworks.com/tag/cloud/ "Cloud") * [Data exfiltration](https://unit42.paloaltonetworks.com/tag/data-exfiltration/ "data exfiltration") [Read now ![Right arrow](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-right-arrow-withtail.svg)](https://unit42.paloaltonetworks.com/autonomous-ai-cloud-attacks/ "Can AI Attack the Cloud? Lessons From Building an Autonomous Cloud Offensive Multi-Agent System") ![Pictorial representation of passwordless authentication. Futuristic cityscape with skyscrapers surrounded by glowing, neon-lit pathways and digital clouds. The sky is vibrant with pink and orange hues, giving a surreal, cyberpunk aesthetic.](https://unit42.paloaltonetworks.com/wp-content/uploads/2026/03/02_Cloud_cybersecurity_research_Overview_1920x900-786x368.jpg) [![category icon](https://unit42.paloaltonetworks.com/wp-content/uploads/2024/06/icon-threat-research.svg)Threat Research](https://unit42.paloaltonetworks.com/category/threat-research/) March 23, 2026 [#### Google Cloud Authenticator: The Hidden Mechanisms of Passwordless Authentication](https://unit42.paloaltonetworks.com/passwordless-authentication/) * [Google](https://unit42.paloaltonetworks.com/tag/google/ "Google") * [Google authenticator](https://unit42.paloaltonetworks.com/tag/google-authenticator/ "google authenticator") * [Google Chrome](https://unit42.paloaltonetworks.com/tag/google-chrome/ "Google Chrome") [Read now ![Right arrow](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-right-arrow-withtail.svg)](https://unit42.paloaltonetworks.com/passwordless-authentication/ "Google Cloud Authenticator: The Hidden Mechanisms of Passwordless Authentication") ![Close-up of a black woman with glasses examining colorful computer code on a screen. The scene is illuminated by various lights, creating a focused and analytical atmosphere.](https://unit42.paloaltonetworks.com/wp-content/uploads/2026/02/13_Cloud_cybersecurity_research_Overview_1920x900-786x368.jpg) [![category icon](https://unit42.paloaltonetworks.com/wp-content/uploads/2024/06/icon-threat-research.svg)Threat Research](https://unit42.paloaltonetworks.com/category/threat-research/) February 6, 2026 [#### Novel Technique to Detect Cloud Threat Actor Operations](https://unit42.paloaltonetworks.com/tracking-threat-groups-through-cloud-logging/) * [API](https://unit42.paloaltonetworks.com/tag/api/ "API") * [IAM](https://unit42.paloaltonetworks.com/tag/iam/ "IAM") * [MITRE](https://unit42.paloaltonetworks.com/tag/mitre/ "MITRE") [Read now ![Right arrow](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-right-arrow-withtail.svg)](https://unit42.paloaltonetworks.com/tracking-threat-groups-through-cloud-logging/ "Novel Technique to Detect Cloud Threat Actor Operations") ![Pictorial representation of Azure OpenAI DNS resolution issue. Futuristic cityscape illustration with luminous structures and floating cloud elements, showcasing advanced technology and a dynamic, digitally enhanced environment.](https://unit42.paloaltonetworks.com/wp-content/uploads/2025/06/02_DNS_Overview_1920x900-786x368.jpg) [![category icon](https://unit42.paloaltonetworks.com/wp-content/uploads/2024/06/icon-threat-research.svg)Threat Research](https://unit42.paloaltonetworks.com/category/threat-research/) January 20, 2026 [#### DNS OverDoS: Are Private Endpoints Too Private?](https://unit42.paloaltonetworks.com/dos-attacks-and-azure-private-endpoint/) * [Microsoft Azure](https://unit42.paloaltonetworks.com/tag/microsoft-azure/ "Microsoft Azure") * [Networking](https://unit42.paloaltonetworks.com/tag/networking/ "networking") [Read now ![Right arrow](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-right-arrow-withtail.svg)](https://unit42.paloaltonetworks.com/dos-attacks-and-azure-private-endpoint/ "DNS OverDoS: Are Private Endpoints Too Private?") ![Pictorial representation of cloud discovery with AzureHound. A digital representation of a cloud composed of blue light particles, superimposed over a blurred background of server racks in a data center.](https://unit42.paloaltonetworks.com/wp-content/uploads/2025/10/08_Cloud_cybersecurity_research_Overview_1920x900-786x368.jpg) [![category icon](https://unit42.paloaltonetworks.com/wp-content/uploads/2024/06/icon-threat-research.svg)Threat Research](https://unit42.paloaltonetworks.com/category/threat-research/) October 24, 2025 [#### Cloud Discovery With AzureHound](https://unit42.paloaltonetworks.com/threat-actor-misuse-of-azurehound/) * [Control plane](https://unit42.paloaltonetworks.com/tag/control-plane/ "control plane") * [Curious Serpens](https://unit42.paloaltonetworks.com/tag/curious-serpens/ "Curious Serpens") * [Data plane](https://unit42.paloaltonetworks.com/tag/data-plane/ "data plane") [Read now ![Right arrow](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-right-arrow-withtail.svg)](https://unit42.paloaltonetworks.com/threat-actor-misuse-of-azurehound/ "Cloud Discovery With AzureHound") ![Pictorial representation of a gift card fraud campaign. A glowing skull and crossbones on a circuit board.](https://unit42.paloaltonetworks.com/wp-content/uploads/2025/10/07_Cybercrime_Category_1920x900-786x368.jpg) [![category icon](https://unit42.paloaltonetworks.com/wp-content/uploads/2024/06/icon-threat-research.svg)Threat Research](https://unit42.paloaltonetworks.com/category/threat-research/) October 22, 2025 [#### Jingle Thief: Inside a Cloud-Based Gift Card Fraud Campaign](https://unit42.paloaltonetworks.com/cloud-based-gift-card-fraud-campaign/) * [CL‑CRI‑1032](https://unit42.paloaltonetworks.com/tag/cl-cri-1032/ "CL‑CRI‑1032") * [Microsoft](https://unit42.paloaltonetworks.com/tag/microsoft/ "Microsoft") * [Phishing](https://unit42.paloaltonetworks.com/tag/phishing/ "phishing") [Read now ![Right arrow](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-right-arrow-withtail.svg)](https://unit42.paloaltonetworks.com/cloud-based-gift-card-fraud-campaign/ "Jingle Thief: Inside a Cloud-Based Gift Card Fraud Campaign") * ![Slider arrow](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/slider-arrow-left.svg) * ![Slider arrow](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/slider-arrow-left.svg) ![Close button](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/close-modal.svg) ![Enlarged Image]() ![Newsletter](https://unit42.paloaltonetworks.com/wp-content/uploads/2026/03/unit42-footer-subscribe-desktop.png) ![UNIT 42 Small Logo](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/palo-alto-logo-small.svg) Get updates from Unit 42 ## Peace of mind comes from staying ahead of threats. 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